Purpose

User parameters:

root_dir = 'C:/Users/ssmal/learning/Projects/financial modeling'
file_loc = f'{root_dir}/data/cheesco-model.xlsm'
actual_dates = ['2016-12-31','2017-12-31','2018-12-31']
forecast_dates = ['2019-12-31','2020-12-31','2021-12-31','2022-12-31','2023-12-31']

Python set-up

from finModel.analysis.ratios import ebitda_revenue_ratio
from finModel.statements.main import FinancialStatement
from finModel.analysis.dcf_valuation import DCFValuation
from extract import source_balance, source_income
import plotly.express as px
import pandas as pd
import numpy as np

statement = FinancialStatement(comp="Cheese Co.",
                               f_date=forecast_dates,
                               inc=source_income(file_loc,actual_dates),
                               bs=source_balance(file_loc,actual_dates))

dcf = DCFValuation(wacc=0.1,lt_growth=0.02,a_date=actual_dates,f_date=forecast_dates,fin=statement)

1. Financial statements

1.1: Income statement

1.2: Balance Sheet

1.3: Cashflow statement

1.4: DCF valuation

2. Visualisation

2.1: Revenues and EBITDA

fig = px.bar(data_frame=ebitda_revenue_ratio(statement.income),x="period",y="Revenues")
fig.show()